Publisher's Synopsis
As cyberattacks continue to grow in complexity and number, computational intelligence is helping under-resourced security analysts stay one step ahead of threats. Drawing on threat intelligence from millions of studies, blogs, and news articles, computational intelligence techniques such as machine learning and automatic natural language processing quickly provide the means to identify real threats and dramatically reduce response times.
The book collects and reports on recent high-quality research addressing different cybersecurity challenges. It:
- explores the newest developments in the use of computational intelligence and AI for cybersecurity applications
- provides several case studies related to computational intelligence techniques for cybersecurity in a wide range of applications (smart health care, blockchain, cyber-physical system, etc.)
- integrates theoretical and practical aspects of computational intelligence for cybersecurity so that any reader, from novice to expert, may understand the book's explanations of key topics.
It offers comprehensive coverage of the essential topics, including:
- machine learning and deep learning for cybersecurity
- blockchain for cybersecurity and privacy
- security engineering for cyber-physical systems
- AI and data analytics techniques for cybersecurity in smart systems
- trust in digital systems
This book discusses the current state-of-the-art and practical solutions for the following cybersecurity and privacy issues using artificial intelligence techniques and cutting-edge technology. Readers interested in learning more about computational intelligence techniques for cybersecurity applications and management will find this book invaluable. They will get insight into potential avenues for future study on these topics and be able to prioritize their efforts better.
